Stochastic scheduling to minimize expected maximum lateness
This paper is concerned with the problems in scheduling a set of jobs associated with random due dates on a single machine so as to minimize the expected maximum lateness in stochastic environment. This is a difficult problem and few efforts have been reported on its solution in the literature. In t...
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| Vydané v: | European journal of operational research Ročník 190; číslo 1; s. 103 - 115 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
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Amsterdam
Elsevier B.V
01.10.2008
Elsevier Elsevier Sequoia S.A |
| Edícia: | European Journal of Operational Research |
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| ISSN: | 0377-2217, 1872-6860 |
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| Abstract | This paper is concerned with the problems in scheduling a set of jobs associated with random due dates on a single machine so as to minimize the expected maximum lateness in stochastic environment. This is a difficult problem and few efforts have been reported on its solution in the literature. In this paper, we first derive a deterministic equivalent to the expected maximum lateness and then propose a dynamic programming algorithm to obtain the optimal solutions. The procedures to compute optimal solutions are initially developed in the case of deterministic processing times, and then extended to stochastic processing times following arbitrary probability distributions. Moreover, several heuristic rules are suggested to compute near-optimal solutions, which are shown to be highly efficient and accurate by computer-based experiments. |
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| AbstractList | This paper is concerned with the problems in scheduling a set of jobs associated with random due dates on a single machine so as to minimize the expected maximum lateness in stochastic environment. This is a difficult problem and few efforts have been reported on its solution in the literature. In this paper, we first derive a deterministic equivalent to the expected maximum lateness and then propose a dynamic programming algorithm to obtain the optimal solutions. The procedures to compute optimal solutions are initially developed in the case of deterministic processing times, and then extended to stochastic processing times following arbitrary probability distributions. Moreover, several heuristic rules are suggested to compute near-optimal solutions, which are shown to be highly efficient and accurate by computer-based experiments. [PUBLICATION ABSTRACT] This paper is concerned with the problems in scheduling a set of jobs associated with random due dates on a single machine so as to minimize the expected maximum lateness in stochastic environment. This is a difficult problem and few efforts have been reported on its solution in the literature. In this paper, we first derive a deterministic equivalent to the expected maximum lateness and then propose a dynamic programming algorithm to obtain the optimal solutions. The procedures to compute optimal solutions are initially developed in the case of deterministic processing times, and then extended to stochastic processing times following arbitrary probability distributions. Moreover, several heuristic rules are suggested to compute near-optimal solutions, which are shown to be highly efficient and accurate by computer-based experiments. |
| Author | Zhou, Xian Wu, Xianyi |
| Author_xml | – sequence: 1 givenname: Xianyi surname: Wu fullname: Wu, Xianyi organization: Department of Statistics, East China Normal University, Shanghai, PR China – sequence: 2 givenname: Xian surname: Zhou fullname: Zhou, Xian email: maxzhou@polyu.edu.hk organization: Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, PR China |
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| Cites_doi | 10.1002/nav.3800210113 10.1287/opre.27.5.925 10.1016/S0952-1976(01)00011-2 10.1016/0020-0190(83)90117-5 10.1007/BF01416077 10.1016/S0895-7177(97)00134-9 10.1016/0377-2217(84)90105-X 10.1287/mnsc.19.5.544 10.1145/322092.322101 10.1007/3-540-08934-9_97 10.1007/s10898-004-5702-z |
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| Keywords | Dynamic programming algorithms Stochastic scheduling Expected maximum lateness Due dates Probabilistic approach Processing time Scheduling Due date Stochastic programming Heuristic method Lateness Dynamic programming Single machine Execution time |
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functions publication-title: Journal of Global Optimization doi: 10.1007/s10898-004-5702-z |
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| SubjectTerms | Applied sciences Due dates Dynamic programming Dynamic programming algorithms Exact sciences and technology Expected maximum lateness Heuristic Job shops Operational research and scientific management Operational research. Management science Scheduling algorithms Scheduling, sequencing Solutions Stochastic models Stochastic scheduling Studies |
| Title | Stochastic scheduling to minimize expected maximum lateness |
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